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Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

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Author Correction: Predicting standardized uptake value of brown adipose tissue from CT scans using convolutional neural networks

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Nature communications 2024年第1期15卷 10022页

作者： Ertunc Erdil Anton S Becker Moritz Schwyzer Borja Martinez-Tellez Jonatan R Ruiz Thomas Sartoretti H Alberto Vargas A Irene Burger Alin Chirindel Damian Wild Nicola Zamboni Bart Deplancke Vincent Gardeux Claudia Irene Maushart Matthias Johannes Betz Christian Wolfrum Ender Konukoglu Computer Vision Lab. ETH Zurich Zurich Switzerland. ertunc.erdil@vision.ee.ethz.ch. Computer Vision Lab. ETH Zurich Zurich Switzerland. Department of Radiology Memorial Sloan Kettering Cancer Center New York NY USA. Institute for Diagnostic and Interventional Radiology University Hospital Zurich Zurich Switzerland. Department of Radiology NYU Grossman School of Medicine New York NY USA. Department of Nursing Physiotherapy and Medicine and SPORT Research Group (CTS-1024) CERNEP Research Center University of Almería Almería Spain. CIBER de Fisiopatología de la Obesidad y Nutrición (CIBEROBN) Instituto de Salud Carlos III Granada Spain. Department of Medicine Division of Endocrinology and Einthoven Laboratory for Experimental Vascular Medicine Leiden University Medical Center Leiden The Netherlands. Department of Physical Education and Sports Faculty of Sports Science Sport and Health University Research Institute (iMUDS) University of Granada 18071 Granada Spain. Instituto de Investigación Biosanitaria Ibs.Granada Granada Spain. Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn) Instituto de Salud Carlos III Madrid Spain. Department of Nuclear Medicine University Zurich Hospital Zurich Switzerland. University of Zurich Zurich Switzerland. Department of Radiology and Nuclear Medicine University Hospital of Basel Basel Switzerland. Swiss Multi-Omics Center ETH Zürich Zürich Switzerland. Laboratory of Systems Biology and Genetics Institute of Bioengineering School of Life Sciences Ecole Polytechnique Fédérale de Lausanne (EPFL) 1015 Lausanne Switzerland. Swiss Institute of Bioinformatics 1015 Lausanne Switzerland. Department of Endocrinology Diabetes and Metabolism University Hospital Basel and University of Basel Basel Switzerland. Department of Health Sciences and Technology ETH Zurich Zurich Switzerland. The LOOP Zürich - Medical Research Center Zürich Switzerland.

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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A thermodynamic framework for modelling membrane transporters

arXiv

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arXiv 2018年

作者： Pan, Michael Gawthrop, Peter J. Tran, Kenneth Cursons, Joseph Crampin, Edmund J. Systems Biology Laboratory School of Mathematics and Statistics Department of Biomedical Engineering Melbourne School of Engineering University of Melbourne ParkvilleVIC3010 Australia Auckland Bioengineering Institute University of Auckland Bioinformatics Division Walter and Eliza Hall Institute of Medical Research ParkvilleVIC3052 Australia Department of Medical Biology School of Medicine University of Melbourne ParkvilleVIC3010 Australia School of Medicine Faculty of Medicine Dentistry and Health Sciences University of Melbourne ParkvilleVIC3010 Australia ARC Centre of Excellence in Convergent Bio-Nano Science and Technology Melbourne School of Engineering University of Melbourne ParkvilleVIC3010 Australia

Membrane transporters contribute to the regulation of the internal environment of cells by translocating substrates across cell membranes. Like all physical systems, the behaviour of membrane transporters is constrained by the laws of thermodynamics. However, many mathematical models of transporters, especially those incorporated into whole-cell models, are not thermodynamically consistent, leading to unrealistic behaviour. In this paper we use a physics-based modelling framework, in which the transfer of energy is explicitly accounted for, to develop thermodynamically consistent models of transporters. We then apply this methodology to model two specific transporters: the cardiac sarcoplasmic/endoplasmic Ca2+ATPase (SERCA) and the cardiac Na+/K+ATPase. Copyright © 2018, The Authors. All rights reserved.

关键词： Energy transfer

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Comparative Study of the Silver Nano-/Microstructures Deposited from Aerosol and Fog

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Advances in Nanoparticles 2017年第3期6卷 128-139页

作者： A. V. Zheltova E. V. Maslyonkova Yu. G. Biryukov P. R. Kasanskii S. M. Ryndya A. S. Smolyanskii Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russia Pirogov Russian National Research Medical University Moscow Russia Branch of JSC “Karpov Institute of Physical Chemistry” Moscow Russia JSC “Systems of Microscopy and Analysis” Moscow Russia National Research Nuclear University “MePhi” Moscow Russia Mendeleev University of Chemical Technology Moscow Russia

A comparative study of the structure and fractal properties of arrays of the silver nano-/micro-particles deposited on the silicon substrate both from the aerosol and fog showed that the form of the silver individual particles and nano-/microstructures greatly depends on the deposition conditions. By passing an aerosol through isopropyl alcohol, the formation of fractal aggregates of the silver nano-/micro-particles both in the air and in alcohol was observed. Deposition of the silver nano-/micro-particles in the atmosphere of the saturated isopropyl alcohol vapours led to formation of fog. Microdroplets of the silver colloidal solution were deposited on the substrate. The further evaporation of alcohol created the silver nano/microstructures in the form of annular layers. It was found that the concerned annular layers contained silver particles of the same shape in the form of a Crescent (or Janus-nano-/microparticles). The nature of discovered effects is discussed.

关键词： Aerosol Fog Silver Deposition Janus-Nanoparticle Fractal Aggregate

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Where are the limits of the centrosome?

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BioArchitecture 2016年第3期6卷 47-52页

作者： Alieva, Irina B. Uzbekov, Rustem E. A. N. Belozersky Institute of Physico-Chemical Biology Moscow State University Moscow Russian Federation Laboratory of Cell Biology and Electron Microscopy Faculty of Medicine François Rabelais University Tours France Faculty of Bioengineering and Bioinformatics Moscow State University Moscow Russian Federation

ABSTRACT: The centrosome is a key component of the cell is involved in the processes of cell division, cell motility, intracellular transport, organization of the microtubules (MT) network and the production of cilia and flagella. The peculiarity of this organelle is that its boundaries are not clearly defined, the centrioles at the center of the centrosome are surrounded by electron dense pericentriolar material, the size and protein composition of this centrosome component experiences significant transformation during the cell cycle. It has been shown in this study that within the centrosome different proteins occupy different areas corresponding to: MT nucleation region (defined as gamma-tubulin-stained area), regulatory region (defined as kinase pEg2-stained area) and motor proteins region (kinesin-like motor XlEg5-stained area). The boundary of pEg2 is near 1.3 times greater while XlEg5 is 3.0 times greater than that of gamma-tubulin. Thus, the size of the centrosome, determined according to the structural electron microscopy (EM) analysis (about 1 µm) corresponds to the regulatory proteins area, but the actual functional centrosome size defined at the motor proteins region, is more than twice the size. © 2016 Taylor & Francis Group, LLC.

关键词： centriole centrosome microtubules mitosis pericentriolar material prophase

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Metagenomic binning reveals versatile nutrient cycling and distinct adaptive features in alphaproteobacterial symbionts of marine sponges

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FEMS MICROBIOLOGY ECOLOGY 2018年第6期94卷

作者： Karimi, Elham Slaby, Beate M. Soares, Andre R. Blom, Jochen Hentschel, Ute Costa, Rodrigo Centre of Marine Sciences (CCMAR) Faculty of Science and Technology (FCT) Algarve University 8005-139 Faro Portugal RD3 Marine Microbiology GEOMAR Helmholtz Centre for Ocean Research Kiel 24105 Kiel Germany Institute of Geography and Earth Sciences Aberystwyth University SY23 3DB Aberystwyth Wales UK Bioinformatics and Systems Biology Justus-Liebig-University Giessen 35392 Giessen Germany RD3 Marine Microbiology GEOMAR Helmholtz Centre for Ocean Research Kiel 24105 Kiel Germany Christian-Albrechts-Universität zu Kiel 24118 Kiel Germany Centre of Marine Sciences (CCMAR) Faculty of Science and Technology (FCT) Algarve University 8005-139 Faro Portugal Institute for Bioengineering and Biosciences (IBB) Instituto Superior Técnico Universidade de Lisboa 1049-001 Lisbon Portugal Corresponding author: Department of Bioengineering Instituto Superior Técnico Av. Rovisco Pais 1 South Tower 8th Floor Room 8.6-22 1049-001 Lisbon Portugal. Tel: +351 21 841 7339 E-mail: rodrigoscosta@tecnico.ulisboa.pt

Marine sponges are early-branched metazoans known to harbor dense and diverse microbial communities. Yet the role of the so far uncultivable alphaproteobacterial lineages that populate these sessile invertebrates remains unclear. We applied a sequence composition-dependent binning approach to assemble one Rhodospirillaceaegenome from the Spongia officinalis microbial metagenome and contrast its functional features with those of closely related sponge-associated and free-living genomes. Both symbiotic and free-living Rhodospirillaceae shared a suite of common features, possessing versatile carbon, nitrogen, sulfur and phosphorus metabolisms. Symbiotic genomes could be distinguished from their free-living counterparts by the lack of chemotaxis and motility traits, enrichment of genes required for the uptake and utilization of organic sulfur compounds-particularly taurine-, higher diversity and abundance of ABC transporters, and a distinct repertoire of genes involved in natural product biosynthesis, plasmid stability, cell detoxification and oxidative stress remediation. These sessile symbionts may more effectively contribute to host fitness via nutrient exchange, and also host detoxification and chemical defense. Considering the worldwide occurrence and high diversity of sponge-associated Rhodospirillaceae verified here using a tailored in silico approach, we suggest that these organisms are not only relevant to holobiont homeostasis but also to nutrient cycling in benthic ecosystems.

关键词： Porifera metagenomics functional genomics Rhodospirillaceae host-microbe interactions sulfur metabolism

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Correction to: Recommendations for the nomenclature of enteroviruses and rhinoviruses

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Archives of virology 2020年第6期165卷 1515页

作者： P Simmonds A E Gorbalenya H Harvala T Hovi N J Knowles A M Lindberg M S Oberste A C Palmenberg G Reuter T Skern C Tapparel K C Wolthers P C Y Woo R Zell Nuffield Department of Experimental Medicine University of Oxford Oxford UK. Peter.Simmonds@ndm.ox.ac.uk. Department of Medical Microbiology Leiden University Medical Center Leiden The Netherlands. Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russia. Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands. National Microbiology Service NHS Blood and Transplant London UK. Finnish Institute for Health and Welfare Helsinki Finland. The Pirbright Institute Pirbright Woking UK. Department of Chemistry and Biomedical Sciences Linnaeus University Kalmar Sweden. Division of Viral Diseases Centers for Disease Control and Prevention Atlanta GA USA. Department of Biochemistry Institute for Molecular Virology Madison WI USA. Department of Medical Microbiology and Immunology Medical School University of Pécs Pecs Hungary. Max Perutz Labs Medical University of Vienna Vienna Austria. Department of Microbiology and Molecular Medicine Faculty of Medicine University of Geneva Geneva Switzerland. Department of Medical Microbiology Academic Medical Center University of Amsterdam Amsterdam The Netherlands. Department of Microbiology The University of Hong Kong Hong Kong SAR China. Division of Experimental Virology Institute of Medical Microbiology Jena University Hospital Jena Germany.

Unfortunately, one of the affiliations of author "A. E. Gorbalenya" was missed in original version. The affiliation is updated here.

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Towards a Unified Framework for Determining Conformational Ensembles of Disordered Proteins

arXiv

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arXiv 2025年

作者： Ghafouri, Hamidreza Kadeřávek, Pavel Melo, Ana M. Aspromonte, Maria Cristina Bernadó, Pau Cortes, Juan Dosztányi, Zsuzsanna Erdos, Gabor Feig, Michael Janson, Giacomo Lindorff-Larsen, Kresten Mulder, Frans A.A. Nagy, Peter Pestell, Richard Piovesan, Damiano Schiavina, Marco Schuler, Benjamin Sibille, Nathalie Tesei, Giulio Tompa, Peter Vendruscolo, Michele Vondrasek, Jiri Vranken, Wim Zidek, Lukas Tosatto, Silvio C.E. Monzon, Alexander Miguel Department of Biomedical Sciences University of Padova Italy Via Ugo Bassi 58/B Padova35131 Italy Masaryk University Kamenice 5 Brno62500 Czech Republic National Centre for Biomolecular Research Faculty of Science Masaryk University Kamenice 5 Brno62500 Czech Republic iBB—Institute for Bioengineering and Biosciences Instituto Superior Técnico Universidade de Lisboa Av. Rovisco Pais Lisboa1049-001 Portugal Laboratory i4HB—Institute for Health and Bioeconomy Instituto Superior Técnico Universidade de Lisboa Av. Rovisco Pais Lisboa1049-001 Portugal Université de Montpellier INSERM CNRS Montpellier34090 France LAAS CNRS Université de Toulouse CNRS ToulouseF-31400 France Department of Biochemistry ELTE Eötvös Loránd University Budapest Hungary Department of Biochemistry and Molecular Biology Michigan State University East LansingMI48824 United States Structural Biology and NMR Laboratory Linderstrøm-Lang Centre for Protein Science Department of Biology University of Copenhagen Ole Maaløes Vej 5 CopenhagenDK-2200 Denmark Johannes Kepler University Institute of Biochemistry Linz4040 Austria Department of Molecular Immunology and Toxicology the National Tumor Biology Laboratory National Institute of Oncology Budapest1122 Hungary Department of Anatomy and Histology HUN-REN UVMB Laboratory of Redox Biology Research Group University of Veterinary Medicine Budapest1078 Hungary Chemistry Coordinating Institute University of Debrecen Debrecen4012 Hungary Baruch S. Blumberg Institute DoylestownPA18902 United States Xavier University School of Medicine at Aruba Oranjestad Aruba The Wistar Institute PhiladelphiaPA19107 United States Cell Cycle Laboratory National Institute of Oncology Budapest1122 Hungary Semmelweis University Budapest1117 Hungary Magnetic Resonance Center Department of Chemistry "Ugo Schiff" University of Florence Via Luigi Sacconi 6 Sesto Fiorentino Florence50019 Italy Department of Biochemistry University of

Disordered proteins play essential roles in myriad cellular processes, yet their structural characterization remains a major challenge due to their dynamic and heterogeneous nature. We here present a community-driven initiative to address this problem by advocating a unified framework for determining conformational ensembles of disordered proteins. Our aim is to integrate state-of-the-art experimental techniques with advanced computational methods, including knowledge-based sampling, enhanced molecular dynamics, and machine learning models. The modular framework comprises three interconnected components: experimental data acquisition, computational ensemble generation, and validation. The systematic development of this framework will ensure the accurate and reproducible determination of conformational ensembles of disordered proteins. We highlight the open challenges necessary to achieve this goal, including force field accuracy, efficient sampling, and environmental dependency, advocating for collaborative benchmarking and standardized protocols. © 2025, CC BY-NC-ND.

关键词： Knowledge acquisition

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FP037 INFLUENCE OF INFLAMMATION ON MMSC:ANTI-INFLAMMATORY PRIMING OR SWITCHING TO INFLAMMATORY PHENOTYPE

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Nephrology Dialysis Transplantation 2018年第SUPPL_1期33卷 i59-i60页

作者： Plotnikov, Egor Danilina, Tatyana Pulkova, Natalya Pevzner, Irina Zorova, Ljubava Silachev, Denis Sukhikh, Gennady Zorov, Dmitry A.N.Belozersky Institute of Physico-Chemical Biology Lomonosov Moscow State University Moscow Russian Federation Laboratory of Molecular Mechanisms of Adaptation National Medical Research Center for Obstetrics Gynecology and Perinatology Moscow Russian Federation Institute of Molecular Medicine Sechenov First Moscow State Medical University Moscow Russian Federation Faculty of Bioengineering and Bioinformatics Lomonosov Moscow State University Moscow Russian Federation

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